Alimenté par : Claudia (ADFI Alsace)
Cet outil s'appuie sur PubMind
Un accès direct à la littérature scientifique via la base PubMed permettant de faciliter la veille sur les enjeux complexes de la santé mentale et du fait religieux : de la neuroscience des croyances à l'étude des abus spirituels, en passant par la prise en charge des traumatismes et des processus de déconversion.
Dernière synchronisation le 07/06/2026
Soc Sci Med . 2026;390 :118889
RATIONALE: Despite record-high overdose deaths in the U.S., most individuals meeting criteria for substance use disorder remain outside formal treatment systems. Stigma is a major contributor to this treatment gap yet remains difficult to study among people who use drugs (PWUD) who are not engaged in clinical care. Social media platforms like Reddit offer a valuable window into the lived experiences of stigma of this population through naturally occurring discourse. This study develops a comprehensive framework for identifying stigma expressions in social media discourse, identifies distinct patterns using computational methods, and examines how these patterns relate to established stigma theory.METHODS: We analyzed over one million posts from six drug-related subreddits using mixed-methods. Large language models with human validation identified and classified stigma-related content across validated dimensions of narrativity, stigma experience, and psycholinguistic features. K-means clustering identified distinct stigma expression patterns (phenotypes), which were then characterized through comprehensive linguistic analysis.RESULTS: Analysis of 1,033,619 posts identified 56, 446 stigma-containing posts and revealed a novel classification - Stigma Perceptions & Commentary (SPC) - which captures the broader discourse on stigma beyond personal experiences. Clustering analysis of these stigma posts plus 5495 non-stigma posts (61,941 total) revealed three distinct phenotypes: Internalized Stigma (34.5%), characterized by self-blame, high narrative agency, and avoidant coping; Public Stigma (38.9%), featuring discrimination from healthcare systems with mixed coping; and Righteous Indignation (26.6%), marked by analytical critique of systemic issues.CONCLUSION: These phenotypes align with theoretical models of self-stigma and demonstrates the potential of social media data to extend stigma research beyond clinical populations, offering insight into how PWUD experience and contest stigma in everyday discourse.